02 · MISSION PROFILE
What we build
Six capabilities, one unit. Each is delivered as working software, not a slide.
CAP-01CONFIDENCE0.98
Platform architecture
The foundation an enterprise needs to build and run agents at scale: orchestration, retrieval, grounding, memory, and tool integration.
CAP-02CONFIDENCE0.97
Agent engineering
Agents and the components around them, built hands-on: multi-agent orchestration, RAG pipelines, function calling, and Model Context Protocol integrations.
CAP-03CONFIDENCE0.96
Model and context engineering
Choosing and routing between models, and engineering the prompts and context that decide how they behave.
CAP-04CONFIDENCE0.99
Evaluation and observability
Testing, evaluation, and monitoring that show whether an agent is doing its job, before launch and after.
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Guardrails and governance
Identity, access control, auditability, data governance, and responsible AI requirements built in from the first commit.
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Enterprise integration
Working with architecture, security, and platform teams so the system fits the organization it has to live in.
> MIND:Confidence figures are illustrative. That one is 1.00.
03 · OPERATING PRINCIPLES
How we work
- SO-01
Measure before trusting
An agent that hasn't been evaluated is a rumor. Evaluation is built alongside the feature.
- SO-02
Constrain the blast radius
Agents get the access they need and no more. Every action leaves a trail.
- SO-03
Boring where it counts
Novel models, conventional engineering. The interesting part should be the capability, never the outage.
- SO-04
Leave it runnable
The client's team should be able to operate, extend, and question everything after the unit departs.
SYSTEMS ABOARD / What we build on
- Azure AI Foundry
- Azure OpenAI
- Azure AI Search
- Microsoft Fabric
- Claude
- Gemini
CREW 01 / FounderSTAKE 100%
01
Daniel Rolfe
Software architectDesigns and builds AI agent platforms for large organizations, from architecture through production code. Works at the intersection of software architecture and applied AI, with a focus on agentic infrastructure, LLM systems, and voice.
- ARCHITECTURE
- AGENTIC AI
- LLM SYSTEMS
- VOICE
SISTER SHIPAlso aboard the GSV Well, It Compiled, a separate vessel. See Vertrus.
> MIND:The org chart is a dot.
DESIGNATION / About the name
Why “Mostly”
Software is supposed to be deterministic. Language models are not. The work happens in the gap: engineering around a probabilistic core until the whole thing is dependable enough to run a business on.
Mostly.
A nod to the ship Minds of Iain M. Banks's Culture novels, who choose their own names.
Building an agent platform, or trying to make one behave? Send a signal. Replies come from the one human aboard.